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Jason Rutherglen commented on HBASE-3529:
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Otis, I think many of your questions have been addressed in this issue, though indeed the
comment trail is long at this point.
bq. Do you have an alternative plan?
https://issues.apache.org/jira/browse/HBASE-3529?focusedCommentId=13040465&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-13040465
bq. Are there issues around distributed search? It looks like it wasn't in your github branch
https://issues.apache.org/jira/browse/HBASE-3529?focusedCommentId=13042913&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-13042913
bq. What about storing the index in HBase itself?
I think that's a great idea to test, though in a different Jira issue.
bq. PKIndexSplitter
That's LUCENE-2919. Given it's not been committed I may need to bring it over into the HBase
search source tree.
> Add search to HBase
> -------------------
>
> Key: HBASE-3529
> URL: https://issues.apache.org/jira/browse/HBASE-3529
> Project: HBase
> Issue Type: Improvement
> Affects Versions: 0.90.0
> Reporter: Jason Rutherglen
> Attachments: HBASE-3529.patch
>
>
> Using the Apache Lucene library we can add freetext search to HBase. The advantages
of this are:
> * HBase is highly scalable and distributed
> * HBase is realtime
> * Lucene is a fast inverted index and will soon be realtime (see LUCENE-2312)
> * Lucene offers many types of queries not currently available in HBase (eg, AND, OR,
NOT, phrase, etc)
> * It's easier to build scalable realtime systems on top of already architecturally sound,
scalable realtime data system, eg, HBase.
> * Scaling realtime search will be as simple as scaling HBase.
> Phase 1 - Indexing:
> * Integrate Lucene into HBase such that an index mirrors a given region. This means
cascading add, update, and deletes between a Lucene index and an HBase region (and vice versa).
> * Define meta-data to mark a region as indexed, and use a Solr schema to allow the user
to define the fields and analyzers.
> * Integrate with the HLog to ensure that index recovery can occur properly (eg, on region
server failure)
> * Mirror region splits with indexes (use Lucene's IndexSplitter?)
> * When a region is written to HDFS, also write the corresponding Lucene index to HDFS.
> * A row key will be the ID of a given Lucene document. The Lucene docstore will explicitly
not be used because the document/row data is stored in HBase. We will need to solve what
the best data structure for efficiently mapping a docid -> row key is. It could be a docstore,
field cache, column stride fields, or some other mechanism.
> * Write unit tests for the above
> Phase 2 - Queries:
> * Enable distributed Lucene queries
> * Regions that have Lucene indexes are inherently available and may be searched on, meaning
there's no need for a separate search related system in Zookeeper.
> * Integrate search with HBase's RPC mechanism
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